Two frameworks can help organizations identify potential harms posed by algorithms, AI tools, or large language models.
Data, AI, & Machine Learning
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Avoid ML Failures by by Asking the Right Questions
Checking assumptions and mapping out work processes can help ensure that ML solutions fit the job to be done.
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How Generative AI Can Support Advanced Analytics Practice
The natural language capabilities of LLMs can augment the predictive powers of advanced analytics.
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Managing Data Privacy Risk in Advanced Analytics
Gaining value from data assets that include customers’ personal information requires advanced data protection tactics.
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How AI Skews Our Sense of Responsibility
When humans are in the loop with an AI system, they may not feel a sense of responsibility to intervene if things go wrong.
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The Hazards of Putting Ethics on Autopilot
Digital nudges can encourage reactive thinking and limit employees’ ethical thinking.
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How Lufthansa Shapes Data-Driven Transformation Leaders
Lufthansa launched an effective program to turn all its leaders into data leaders and propel its digital transformation.
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AI and Statistics: Perfect Together
Business leaders can identify and avoid flawed AI models by employing statistical methods and statistics experts.
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Why Executives Can’t Get Comfortable With AI
In the age of artificial intelligence, executives must make maintaining their AI literacy a habit.
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Reinventing the Organization for GenAI and LLMs
Learn three principles for reorganizing work around AI.